{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,20]],"date-time":"2025-12-20T22:19:23Z","timestamp":1766269163304,"version":"build-2065373602"},"reference-count":42,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2019,2,8]],"date-time":"2019-02-08T00:00:00Z","timestamp":1549584000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"the State Key Program of National Natural Science Foundation of China","award":["41730109"],"award-info":[{"award-number":["41730109"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The objective of the study was to put forth an interpolation method (the LZ method) for refining the GNSS-derived precipitable water vapor (PWV) map. We established a regional weighted mean temperature (Tm) model for this experiment, which introduced a minor difference into the resultant GNSS-derived PWV compared to the previous Tm models. The kernel of the LZ method consists of increasing the sample density via the virtual sample points. These virtual sample points originated from the digital elevation model (DEM) were constructed on the basis of the statistically significant correlation between PWV and geographical location (i.e., geographical coordinates and elevation). The LZ method was validated and compared to the conventional interpolation approach only accounting for the original sample points. The results reflect that the PWV maps generated by the LZ method showed more details than through conventional one. In addition, the prediction performance of the LZ method was better than that of the conventional method by using cross-validation.<\/jats:p>","DOI":"10.3390\/s19030698","type":"journal-article","created":{"date-parts":[[2019,2,11]],"date-time":"2019-02-11T03:26:01Z","timestamp":1549855561000},"page":"698","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["A New Method for Refining the GNSS-Derived Precipitable Water Vapor Map"],"prefix":"10.3390","volume":"19","author":[{"given":"Chen","family":"Liu","sequence":"first","affiliation":[{"name":"Jiangsu Key Laboratory of Resources and Environmental Information Engineering, China University of Mining and Technology, Xuzhou 221116, China"},{"name":"School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China"}]},{"given":"Nanshan","family":"Zheng","sequence":"additional","affiliation":[{"name":"Jiangsu Key Laboratory of Resources and Environmental Information Engineering, China University of Mining and Technology, Xuzhou 221116, China"},{"name":"School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9376-1148","authenticated-orcid":false,"given":"Kefei","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China"},{"name":"SPACE Research Centre, School of Science, RMIT University, Melbourne VIC 3001, Australia"}]},{"given":"Junyu","family":"Liu","sequence":"additional","affiliation":[{"name":"College of Engineering, Northeastern University, Boston, MA 02115, USA"}]}],"member":"1968","published-online":{"date-parts":[[2019,2,8]]},"reference":[{"key":"ref_1","first-page":"D18103","article-title":"Precipitable water vapor characterization in the Gulf of Cadiz region (southwestern spain) based on Sun photometer, GPS, and radiosonde data","volume":"115","author":"Torres","year":"2010","journal-title":"J. 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